Data for Serial Dependence in face-gender classification revealed in low-beta frequency EEG: Ranieri, Burr, Bell, and Morrone

The neurophysiological mechanisms of how past perceptual experience affects current perception are poorly understood. Using classification techniques, we demonstrate that the response to gender of the previous face image of a sequence can be decoded from the neural activity of the current EEG response, showing that relevant neural signals are maintained over trials. Classification accuracy was higher for participants with strong serial dependence, strongly implicating these signals as the neural substrate for serial dependence. The best information to classify gender was around 14 Hz for “female” faces, and around 18 Hz for “male”, reinforcing the psychophysical results showing serial dependence to be carried at those beta-frequencies.